BEGIN:VCALENDAR VERSION:2.0 PRODID:-//KnowAFest//Campus Events//EN BEGIN:VEVENT UID:eventsphere-55025@www.knowafest.com DTSTAMP:20261008T163732Z DTSTART:20190725T183000Z DTEND:20190726T182959Z SUMMARY:Recent Trends and Challenges in Bayesian Statistics for Big Data an alytics 2019 LOCATION:Kongu Engineering College\, Erode DESCRIPTION:

We live in an era of Big Data\, where Science\, Engineering and Technology are producing massive data streams\, with petabyte and exab yte scales becoming increasingly common. Besides the explosive growth in v olume\, Big Data also has high velocity\, high variety and high uncertaint y. These complex data streams require ever-increasing processing speed\, e conomical storage and timely response for decision making in highly uncert ain environments and have raised various challenges to the conventional da ta analysis. With the primary goal of building intelligent systems that au tomatically improve from experiences\, machine learning is becoming an inc reasingly important field to tackle the Big Data challenges\, with the eme rging field of Big Learning which covers theories\, algorithms and systems on addressing big data problems. Bayesian methods represent one important class of statistical methods for machine learning\, with substantial rece nt developments in adaptive\, flexible and scalable Bayesian learning.
\nBayesian methods are becoming increasingly relevant in the era of Big Data to protect high capacity models against overfitting and to allow mode ls to adaptively update their capacity. However\, their application to Big Data problems create a computational bottleneck that needs to be addresse d with new inference methods. Bayesian methods are conceptually simple and flexible hierarchical Bayesian modeling offers a flexible tool for charac terizing uncertainty\, missing values\, latent structures and more. Moreov er\, regularized Bayesian inference further augments the flexibility by in troducing an extra dimension to incorporate domain knowledge or to optimiz e a learning objective.
\nThis seminar focuses on the mathematical th eory and computational tools utilized in Bayesian modeling\, inference and machine learning. Applications for Bayesian Statistics will be drawn chie fly from weather and ocean prediction\, autonomous vehicles and socio-tech nical systems. While interdisciplinary training has generally been frowned upon\, this seminar acts as a forum for the intersection of Mathematician s and Engineers\, thus improving communication among various disciplines.< /p> URL:https://www.knowafest.com/recent-trends-and-challenges-in-bayesian-stat istics-for-big-data-analytics-2019 END:VEVENT END:VCALENDAR